What's the difference between MCP and RAG?

RAG pulls outside material into the model’s context before it answers; MCP lets an agent discover and call a tool. A retriever can be that tool. The retrieval pipeline can be fully managed, and the MCP server can be one you run yourself, so neither term tells you whose deployment it is.

A stale retrieved chunk can make the answer wrong whether the agent reached the retriever through MCP or not. A changed MCP tool schema can stop the call before retrieval even starts. Whether retrieval runs automatically or gets called as a tool is separate from both.

sources

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More on this.

How do I cancel an in-flight MCP tool call?Send a notifications/cancelled message naming the request id; the server stops and skips a response, but a reply can still arrive if it crosses the cancel.answer →How do I evaluate an MCP server's reliability?Test the four ways an MCP server fails on purpose: a failed tool result, a schema that changes mid-session, a stalled response, and a cancel, each checked.answer →How do I set a timeout on an MCP tool call?Set a per-request timeout in your client SDK and cancel on expiry; the spec lets a progress notification reset the clock, but a hard maximum should still apply.answer →Everything on mcp tool reliabilityThe definition, and every question answered under mcp tool reliability.concept →

Two ways to run Tessary.

Tessary is an open-source agent reliability platform. Cloud and self-hosted run the same workflow on the OpenTelemetry traces your agent already emits.

Tessary Cloud

We host it for you. Send your first trace with nothing to deploy and no model key.

what's includedper organization
traces
10,000 per calendar month
stored trace data
1 GB
retention
30 days
model credit
$10, one-time, for triage and root-cause analysis
credit card
not required
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Self-hosted Tessary

Run the open-source code on your own infrastructure with one command. Add your own model key for triage and root-cause analysis.

Self-host Tessary for me by following https://github.com/tessaryai/tessary/blob/main/setup.md

docker compose -f oci://docker.io/tessaryai/tessary:compose up -d -y